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The following segment was excerpted from this fund letter.
In 1967, leading scientists and engineers inside the Dutch conglomerate Philips (PHG) had a tremendous achievement to showcase at the company’s annual research exhibition. They had developed a six-barrel step-and-repeat camera system for semiconductor manufacturing—essentially, the predecessor to the lithography machines used today. Although the exhibit initially attracted a large crowd of fellow researchers and top Philips executives, it wasn’t long before the executives turned their attention to a nearby booth that was displaying new features of a different product, the washing machine.
In the decades that followed, Philips became a leader in consumer electronics and health-care equipment, and the camera system technology—a tiny moonshot project it never seemed to prioritize— became ASML, a leading supplier of the intricate machinery used to produce semiconductor chips. The latter continued to take innovative leaps, and it has been rewarded. ASML now has a market value nearly 20 times larger than that of its former parent.
This quarter, nothing—certainly not washing machines—could divert attention away from ASML or its peers Nvidia (NVDA) and TSMC (TSM). The three semiconductor stocks were responsible for a disproportionately large percentage of the overall market return. Two of them, ASML and TSMC, have been portfolio holdings since 2021, while we exited Nvidia in the first quarter after more than five years. Their strong performance is quite deserving, given that the competitive structure of their industry, oligopoly or near monopoly, is more favorable than most we encounter. But just a few years ago, as the personal computer and mobile phone cycles ran their course, the outlook for chip demand was much less sanguine.
The tech world has long subscribed to Moore’s Law, an observation and prediction that the number of transistors on an integrated circuit doubles every two years with a minimal rise in cost. But as it has become increasingly difficult and costly to shrink the size of transistors any further, the fear has been that without a technological breakthrough, the computational power of chips will hit a ceiling. One promising technology that has emerged to counter this fear is extreme ultraviolet (‘EUV’) lithography.
Think of a lithography machine as a large camera that uses light to transfer precise patterns onto a wafer’s surface, which is then diced into chips. The shorter wavelengths of EUV radiation can print a sharper image of tinier details, thus allowing for smaller transistors. But using a different light source also created a host of challenges that had to be solved. After spending years working to improve the performance of its EUV machines, from throughput to overlay accuracy to uptime, ASML has now shipped more than 100 of them to customers, with some configurations costing well north of US$100 million. As it was working to perfect these EUV machines, ASML also began to develop a next-generation technology called High NA (for numerical aperture), which can print even finer features on a wafer. After a decade of research and development, it shipped its first High NA machine in December 2023, leaving its competitors even further behind. With these tools, the semiconductor industry can potentially develop more powerful and energy-efficient chips to meet the surging demand for computing power coming from fields such as AI, autonomous driving, and the internet of things.
Shrinking the transistor through innovations in lithography is still just one step to produce more powerful chips. The transistors also need to become more interconnected, thus allowing for a higher number of them to sit on a single chip (our Fundamental Thinking article “Third Law: How a Pair of Chip Companies Came to Hold the Keys to Everything” details this trend). In April, TSMC unveiled its plan to do this, which will advance chip technology by two generations—from the current N3 (three nanometer), to N2, and then to A16 (meaning 1.6 nanometers, or 16 angstrom). Currently, a typical graphics processing unit (GPU) used to train an AI model has over 100 billion transistors. TSMC Chairman Mark Liu forecasts that within a decade that figure will rise to more than 1 trillion. Such a steep trajectory is a great manufacturing challenge, and if the company is successful, it will be a great testimony to TSMC’s engineering capabilities.
Even with such a formidable position, these industry leaders have had their share of ups and downs. We don’t believe we can add much value in trying to predict industry cycles or time the tipping point of demand—whether for hardware companies such as ASML and Nvidia or the software and IT services companies we wrote about last quarter, such as Adobe (ADBE), Salesforce (CRM), Accenture (ACN), and Globant (GLOB). Earlier this year, several software and services companies reported disappointing earnings, as overall IT spending remains muted amid high interest rates and ongoing economic and geopolitical uncertainty. But secular growth appears to be underpinned by the innovations described above, as well as the race to introduce value-added tools that use AI to solve business problems. Although the market remains enamored with Nvidia, which trades at a high price-to-earnings ratio, we continue to believe that as large companies embrace generative AI, software and services businesses will become primary beneficiaries of the AI trend.
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Past performance does not guarantee future results. Invested capital is at risk of loss. Please read the above performance in conjunction with the footnotes on the last page of this report. All performance and data shown are in US dollar terms, unless otherwise noted. The portfolio is actively managed therefore holdings identified above do not represent all of the securities held in the portfolio and holdings may not be current. It should not be assumed that investment in the securities identified has been or will be profitable. The following information is available upon request: (1) information describing the methodology of the contribution data in the tables above; and (2) a list showing the weight and relative contribution of all holdings during the quarter and the last 12 months. Past performance does not guarantee future results. In the tables above, “weight” is the average percentage weight of the holding during the period, and “contribution” is the contribution to overall relative performance over the period. Performance of contributors and detractors is net of fees, which is calculated by taking the difference between net and gross composite performance for the Global Equity strategy prorated by asset weight in the portfolio and subtracted from eachsecurity’s return. Contributors and detractors exclude cash and securities in the composite not held in the model portfolio. Quarterly data is not annualized. Portfolio attribution and characteristics are supplemental information only and complement the fully compliant Global Equity Composite GIPS Presentation. Portfolio holdings should not be considered recommendations to buy or sell any security. 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Composite performance is presented gross of foreign withholding taxes ondividends, interest income and capital gains. Additional information is available upon request. Past performance does not guarantee future results. Policies for valuing investments, calculating performance, and preparing GIPS Reports are available upon request. The US dollar is the currency used to express performance. Returns are presented both gross and net of management fees and include the reinvestment of all income. Net returns are calculated using actual fees. Actual returns will be reduced by investment advisory fees and other expenses that may be incurred in the management of the account. The standard fee schedule generally applied to separate Global Equity accounts is 1.00% annually of the market value for the first $20 million; 0.50% for the next $80 million; 0.45% for the next $150 million; 0.40% for the next $250 million; above $500 million upon request. The management fee schedule and total expense ratio for the Global Equity Collective Investment Fund, which is included in the composite, are 0.70% on all assets and 0.75%, respectively. Actual investment advisory fees incurred by clients may vary. The annual composite dispersion presented is an asset-weighted standard deviation calculated for the accounts in thecomposite the entire year. The Global Equity composite was created on November 30, 1989 and the performance inception date is December 1, 1989. |
Editor’s Note: The summary bullets for this article were chosen by Seeking Alpha editors.
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